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ISTQB-Level-1 history - American Software Testing Qualifications Board Level 1 Updated: 2023
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ISTQB-Level-1 American Software Testing Qualifications Board Level 1
Exam: ISTQB-Level-1 (American Software Testing Qualifications Board Level 1)
Exam Details:
- Number of Questions: The test consists of multiple-choice questions.
- Time: Candidates are given a specified amount of time to complete the exam.
Course Outline:
The ISTQB Level 1 certification, provided by the American Software Testing Qualifications Board (ASTQB), is designed for individuals who are new to software testing or have limited experience in the field. The course covers the fundamental principles and techniques of software testing. The course outline includes the following topics:
1. Fundamentals of Testing
- Testing terminology and principles
- Psychology of testing
- Test process and lifecycle
- Test levels and types
2. Testing throughout the Software Development Lifecycle
- Requirements analysis and test design
- Test implementation and execution
- Test closure activities
- Test environment and test data management
3. Static Techniques
- Static testing fundamentals
- Review process and techniques
- Static analysis tools
4. Test Design Techniques
- Black-box and white-box test design techniques
- Equivalence partitioning and boundary value analysis
- Decision table testing and state transition testing
- Use case testing and user story testing
5. Test Management
- Test planning and estimation
- Test progress monitoring and control
- Configuration management and risk management
- Incident management and defect tracking
Exam Objectives:
The ISTQB-Level-1 test aims to assess candidates' understanding of fundamental software testing concepts and their ability to apply them in practical scenarios. The test objectives include:
1. Demonstrating knowledge of testing terminology, principles, and processes.
2. Understanding the different test levels, types, and techniques.
3. Applying static testing techniques and conducting effective reviews.
4. Designing test cases using various black-box and white-box techniques.
5. Understanding test management activities, including planning, monitoring, and control.
Exam Syllabus:
The test syllabus covers the following topics:
- Fundamentals of Testing
- Testing terminology and principles
- Psychology of testing
- Test process and lifecycle
- Test levels and types
- Testing throughout the Software Development Lifecycle
- Requirements analysis and test design
- Test implementation and execution
- Test closure activities
- Test environment and test data management
- Static Techniques
- Static testing fundamentals
- Review process and techniques
- Static analysis tools
- Test Design Techniques
- Black-box and white-box test design techniques
- Equivalence partitioning and boundary value analysis
- Decision table testing and state transition testing
- Use case testing and user story testing
- Test Management
- Test planning and estimation
- Test progress monitoring and control
- Configuration management and risk management
- Incident management and defect tracking
Candidates are expected to have a solid understanding of these subjects and demonstrate their ability to apply the concepts and techniques in real-world testing scenarios. The test assesses their knowledge, skills, and ability to perform software testing activities at a foundational level.
ASTQB Qualifications history
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American Software Testing Qualifications Board Level
1
https://killexams.com/pass4sure/exam-detail/ISTQB-Level-1
Question: 46
Comparing TMMi and TPI, which is not a valid reason for choosing either TPI or
TMMi? 2 credits
A. If the scope of test performance improvement covers all test levels, TMMi is
preferred since TPI focusses mainly on black-box testing.
B. If the organization is already applying CMMI, TMMi may be preferred since it
has the same structure and uses the same terminology. TMMi addresses
management commitment very strongly and is therefore more suitable to support a
top-down improvement process.
C. TPI is much more a bottom-up model that is suitable for addressing test subjects for
a specific (test) project.
D. TMMi can only be used with the traditional V model,whereas TPI can be used
with all types of software life cycles.
Answer: D
Question: 47
A test assessment has been carried out using the selected model as a reference
framework. A number of recommendations have been identified and you are asked
to prioritize them. Based on your knowledge of the project, you are expecting
severe resistance to change. Which of the following would be the most important
selection criterion for defining the priority of the recommendations? 2 credits
A. Synchronized with the overall long-term organizational strategy
B. Defined according to the maturity model used
C. Most visible to stakeholders
D. Low costs actions first
Answer: C
Section 14: Sec Fourteen (48 to 49)
Details:Topic 8, Scenario 8, V2 "Test Proems Improvement'
You have raised the issue that improving the testing process is also dependent on the
status of the software development process.
Question: 48
During test process improvement it is recommended to use standards where
possible. Standards originate from various sources and they cover different subjects
21
in relation to testing Pick TWO sources of software standards, useful to software
testing from the ones mentioned below. 1 credit
A. ISO 9126-1 ‘Software engineering- Product quality Part 1:
Quality model’ is an international standard, that provides a basis on which to
define quality assurance solutions.
B. ISA 4126-1 ‘Software engineering- Product quality Part 1:
Quality model’ is an international standard, that provides a basis on which to
define quality assurance solutions.
C. BS-7925-2 ‘Software testing. Software component testing is a national
standard used internationally. It covers a number of testing techniques that may be
useful both on component testing level and on system testing level.
D. SY-395-01 ‘Standard for East Coast Hospital software’ is a regional standard
adapted from a national one. Besides hospital software, this standard ought to be
used also by other types of software system in the region.
E. IEEE 829 ‘standard for software test documentation’ is an international standard
to be following mandatory by all testing origination regardless of lifecycle models.
Answer: A, C
Question: 49
Which of the following phases in the fundamental test process is considered to
deliver a document which can be used as a major input for test process
improvement? 1 credit
A. Test planning and control
B. Test implementation & execution
C. Evaluating exit criteria and reporting
D. Test project closure
Answer: D
Section 15: Sec Fifteen (50 to 53)
Details:Topic 9, Scenario 9 "Test Management Documentation"
A software house is concerned about the number of defects found in software
released to its customers. They are starting to plan a new software product. In the
past, releases have often been stopped due to poor planning and too many defects
found during high level testing. You have been recruited to the newly created
22
position of test manager and asked to develop a test strategy, manage the testing of
the project and organize the resources needed to carry out the testing.
Question: 50
Which THREE activities would be valid steps during the development of the test
strategy?2 credits (2 out of 3 correct 1 credit)
A. Identify test staff members that will be involved in the system test
B. Define test career paths
C. Understand the software development life cycle used by the software house
D. Assess the testing that needs to be done to minimize the risks
E. Issue the test strategy document for review
F. Define a master test plan template
G. Perform a project risk analysis
Answer: C, D, E
Question: 51
As part of the test strategy, entry and exit criteria will be defined for each test level.
Which is NOT a valid reason for using entry and exit criteria? 1 credit
A. The expectation is that development testing is not adequate.
B. Exit criteria are used to decide on when to stop testing.
C. Entry and exit criteria are a principal way for getting adequate resources.
D. Using entry and exit criteria will prevent software that is not or poorly tested
from going to the next test level.
Answer: C
Question: 52
Within the projects, a master test plan and phase test plan will be used. Following
is a list of characteristics applicable for test plans:
a. Any deviation from the procedures described in the test strategy document b. The
overall estimated costs, timescales and resource requirements
c. A detailed schedule of testing activities
d. The development deliverables to be tested
e. Which test staff members (names) will be involved and when f. Level of
requirements coverage achieved
23
Which THREE of the above mentioned characteristics relate to the master test plan?
1 credit
A. a
B. b
C. c
D. d
E. e
F. f
Answer: A, B, D
Question: 53
Within the projects, a master test plan and phase test plan will be used. Following
is a list of characteristics applicable for test plans:
a. Any deviation from the procedures described in the test b. strategy document
c. The overall estimated costs, timescales and resource d. requirements
e. A detailed schedule of testing activities
f. The development deliverables to be tested
g. Which test staff members (names) will be involved and when h. Level of
requirements coverage achieved
Which TWO of the above mentioned characteristics relate to the phase test plan? 1
credit
A. a
B. b
C. c
D. d
E. e
F. f
Answer: C, E
Section 16: Sec Sixteen (54 to 55)
Details:Topic 10, Scenario 10, V1 "Online Application"
There is a formal requirement from the business to develop an additional on-line
application to the company website which will allow existing policyholders to
extend their cover for short-term foreign use of their vehicle overseas. The current
manual process will be retained. The application must be implemented in months
time in line with the marketing department's green initiative, which is anticipated to
generate a significant increase in demand.
24
The development manager has insufficient resources to meet this request and
has issued an invitation to potential bidders so that the development work can be
outsourced.
The application must initially cover Western Europe, and later Eastern Europe,
Russia, the Middle East, the Far East and Africa. A decision has yet to be made with
respect to Australia, New Zealand, North and South America.
You have been asked to ensure the quality and suitability of the document sent to
potential bidders and also that the application delivered by the successful bidder is
‘Tit for purpose’.
Question: 54
Which of the following product risks would be most effectively addressed just by
static testing? 3 credits
A. In the delivered application, one of the countries, as specified in the
requirements, has not been correctly implemented.
B. The application takes too long to process a request for additional cover.
C. The test cases do not cover the key requirements.
D. The successful bidder may not deliver all the required functionality on time.
Answer: C
Question: 55
The development manager is managing the review of the responses received from
bidders, and has asked the in-house test manager to provide a review checklist for
the test management aspects of the responses. Which of the following checkpoints
would be appropriate? 2 credits
A. The bidder’s test policy should enforce that incident management fully conforms
to IEEE 1044.
B. The bidder’s project strategy shows that the data content of all the test
environments conforms to EU standards.
C. The bidder’s test plan shows that the application will be delivered for acceptance
in six months time.
D. The bidder’s project test plan depicts a phased implementation with later delivery
dates to be confirmed and states that test deliverables will be developed using IEEE
829 as a guide.
Answer: D
25
Section 17: Sec Seventeen (56 to 56)
Details:Topic 10, Scenario 10, V2 "Online Application"
While waiting for the responses, the test manager has been asked to prepare test
plans to validate the software application delivered by the successful bidder.
Question: 56
Which one of the following estimation approaches is appropriate at this stage of the
project? 2 credits
A. Create an estimate based on the function point analysis technique and test point
analysis
B. Create an estimate based on the complexity of the code
C. Create an estimate based on the credentials of the successful bidder
D. Create an estimate based on a percentage of the development effort
Answer: A
Section 18: Sec Eighteen (57 to 60)
Details:Topic 10, Scenario 10, V3 "Online Application"
The cancellation of a current major development project has released resources. The
development manager has decided to respond to his own request to tender and
has proposed an in-house development with the use of a Rapid Application
Development (RAO) approach.
Question: 57
Why might a RAD approach be a better option for the test manager rather than a
sequential development? 2 credits
A. It will extend the development team’s abilities and enhance future delivery
capabilities.
B. It will allow the marketing, clerical and testing staff to validate and verify the
early screen prototypes.
C. Time-box constraints will ensure code releases are delivered on schedule.
D. More time can be spent on test execution as less formal documentation is
required.
Answer: B
26
Question: 58
Which of the following is NOT a typical key challenge for testing in a RAD based
development approach? 1 credit
A. Re-usable test scripts for (automated) regression testing
B. Project management and control
C. No complete requirements specification
D. Time-boxing
Answer: B
Question: 59
As a result of the RAD based development approach, the test manager has decided
to change the risk mitigation approach. Which test technique might be most
appropriate to use? 2 credits
A. Decision Table Testing
B. Boundary Value Analysis
C. Error Guessing
D. Exploratory Testing
Answer: D
Question: 60
The business has asked for a weekly progress report. Which of the following would
be appropriate as a measure of test coverage? 2 credits
A. Percentage of business requirements exercised
B. Percentage of planned hours worked this week
C. Percentage of countries that have test scenarios
D. Percentage of test iterations completed
Answer: A
Section 19: Sec Nineteen (61 to 61)
27
Details:Topic 11, Scenario 11 "Incident Management"
The following is the current incident handling process in used at the company. Step
1: Incident is documented in the incident Tile with the following information:
- Software module or area where the fault occurred
- Who has reported the fault
- Hardware configuration used for the test that found the fault
- The sequential incident number (1 greater than the last one recorded) Step 2:
Developer assigned to fix the fault
Step 3: Developer fixes the fault
Step 4: Developer signs off the incident as closed, and it is then removed from the
incident file
Question: 61
Regarding the process described above, what is the most important recommendation
you would make using IEEE 1044 as a guide? 2 credits
A. No priority or severity assigned
B. Incident numbering is manual rather than automated
C. No mentioning of reproduceability
D. No classification on type of incident
Answer: A
Section 20: Sec Twenty (62 to 65)
Details:Topic 12, Scenario 12 “Automatic Teller Machine (ATM)”
You are a test manager in charge of integration, system and acceptance testing for a
bank. You are working on a project to upgrade an existing ATM to allow customers
to obtain cash advances from supported credit cards. The system should allow cash
advances from €20 to €500, inclusively, for all supported credit cards. The
supported credit cards are American Express, VISA, Eurocard and Mastercard.
In the master test plan the following items are listed in the section named “items
and/or features to be tested”:
I All supported credit cards
II Language localization
II Valid and invalid advances
IV Usability
V Response time
Question: 62
28
Relying only on the information provided in the scenario, select the TWO items
and/or features for which sufficient information is available to proceed with test
design. 2 credits
A. All supported credit cards
B. Language localization
C. Valid and invalid advances
D. Usability
E. Response time
Answer: A,
Question: 63
Continuing with the Scenario described in the previous question, which of the
following subjects would you need to address in detail in the master test plan? 3
credits
A. An approach to regression testing
B. A list of boundary values for “advance amount”
C. A description of dependencies between test cases
D. A logical collection of test cases
Answer: A
Question: 64
Given the following figures for the testing on a project, and assuming the failure rate
for initial tests remains constant and that all retests pass, what number of tests
remain to be run? 3 credits
A. 700
B. 720
C. 784
D. 570
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Answer: B
Question: 65
Given is the following defect removal chart reported at the end of system testing -
showing total defects detected and closed defects (fixed and successfully retested).
A number of open defects are classified as critical. All tests have been executed.
Based on the chart above, what is the most appropriate next test phase? 1 credit
A. Acceptance testing to verify the business process
B. Acceptance testing to verify operational requirements
C. Requirements testing as part of testing regulatory compliance
D. Another system test cycle to verify defect resolution
Answer: D
30
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Founded originally as Gainesville Junior College in March 1964, the college was the result of visionary community leaders who sought to fill a need for accessible, quality higher education for Northeast Georgians. While a campus was in development, the college initially held classes at the Gainesville Civic Center and First Baptist Church.
In 1966, Gainesville Junior College moved to its permanent campus. With an aim to prepare students for the local workforce or to transfer on to other senior institutions, Gainesville Junior College experienced high demand from the outset. It promoted an educational experience that included academics, athletics, student activities, and public service.
Drawing students primarily from the region surrounding Lake Lanier, the college's logo incorporated an anchor symbol and blue and gold colors. The college's athletic teams competed as The Lakers until the 1985-86 academic year, when intercollegiate athletics were discontinued due to lack of spectator support and a reallocation of institutional resources.
In 1987, the University System of Georgia Board of Regents authorized the removal of "Junior" or "Community" from the two names of two-year institutions to better reflect the quality of the educational experiences students in those colleges received. Gainesville Junior College became Gainesville College.
In 1998, the college adopted a new logo that replaced the anchor previously used to represent the college with a symbolic bell tower that greeted students as they entered campus. The college's colors, too, changed from blue and gold to green.
In 2003, the college expanded to include the Oconee Campus in Watkinsville, Ga., where enrollment grew quickly.
In 2005, the institution's name changed to Gainesville State College, reflecting the growth of four-year degree programs within the college.
The college's historic seal incorporates the State of Georgia seal, an anchor symbolizing the college's first mascot – The Lakers, and the lake in the background symbolizing the Lanier Land service area.
Celebrations in June 2023 marked the 75th anniversary of the arrival HMT Empire Windrush, which brought migrants from the Caribbean to the UK
October marks Black History Month in the UK.
The event began in the US in the 1920s, and was first celebrated in the UK in 1987.
It also takes place in Canada, Germany and Ireland.
When is Black History Month and what is it?
In the UK, Black History Month happens every October.
It gives everyone the opportunity to share, celebrate and understand the impact of black heritage and culture.
People from African and Caribbean backgrounds have been a fundamental part of British history for centuries. However, campaigners believe their contribution to society has often been overlooked or distorted.
How did Black History Month start?
The event was the brainchild of Carter G Woodson, known as the father of black history.
Born in Virginia in 1875 to parents who were former slaves, he had limited access to education and job opportunities. But he was able to study at one of the few high schools for black students after saving money earned by working as a coal miner.
Carter G Woodson launched the first Black History Week in 1926
Woodson went on to gain various qualifications, including a PhD in history from Harvard University, and became a professor at Howard University.
Throughout his life, he worked tirelessly to promote black history in schools.
In 1926 he launched the first Black History Week, set in February to coincide with the births of former President Abraham Lincoln and Frederick Douglass. Both men played a significant role in helping to end slavery.
The event was expanded in 1970, and since 1976 every US president has officially designated February as Black History Month.
A separate holiday - "Juneteenth", held on 19 June - commemorates the end of slavery in the US.
How did Black History Month start in the UK?
The first Black History Month in the UK took place in 1987, the 150th anniversary of the abolition of slavery in the Caribbean.
It was arranged by Akyaaba Addai-Sebo, who came to the UK from Ghana as a refugee in 1984. Like Woodson before him, he wanted to challenge racism and celebrate the history of black people.
October was chosen partly because it's traditionally a time when African leaders gather to talk about important issues, and partly because it was at the start of the school year.
How is Black History Month celebrated in the UK?
When Black History Month first began, there was a big focus on black American history. Over time the event has prioritised black British history and key black figures from the UK, such as:
- Walter Tull, the first black officer to command white troops in the British Army, and one of English football's first black players
- Malorie Blackman, bestselling author and the first black Children's Laureate
- Shirley J Thompson, leading composer and conductor
- Lewis Hamilton, the only black driver in Formula One
Shirley J Thompson composed music for King Charles's coronation
Black History Month is also celebrated in local communities, where museums, care homes and workplaces explore a broad range of topics, from Britain's colonial past to migration and music.
For 2023, people are being encouraged to find out more about the exceptional achievements of black women, especially those who have been forgotten.
There is a national poetry competition, open to primary, secondary, college, and university students across the UK.
The contribution of the Windrush generation is also being celebrated, 75 years after the arrival of passengers on HMT Empire Windrush to the UK.
Is black history taught in schools?
For many children in the UK, October is the only time of the year they will learn about black history.
Wales became the first nation in the UK to introduce mandatory changes to its curriculum in 2022, including lessons about black history, racism and contributions of figures from black, Asian and other ethnic minorities.
Walter Tull played for Tottenham Hotspurs and Northampton Town before he died on the battlefields of World War One
Education is a devolved issue and in England there are no such plans to make changes.
The UK government says black history is an important topic, and that schools have the freedom to teach it within the existing history curriculum, from primary-school age onwards.
Video:
Causes of the Civil War
The causes of the Civil War and its cost to a young nation.
More from Wes about the causes of the Civil War.
What led to the outbreak of the bloodiest conflict in the history of North America?
A common explanation is that the Civil War was fought over the moral issue of slavery.
In fact, it was the economics of slavery and political control of that system that was central to the conflict.
A key issue was states' rights.
The Southern states wanted to assert their authority over the federal government so they could abolish federal laws they didn't support, especially laws interfering with the South's right to keep slaves and take them wherever they wished.
Another factor was territorial expansion.
The South wished to take slavery into the western territories, while the North was committed to keeping them open to white labor alone.
Meanwhile, the newly formed Republican party, whose members were strongly opposed to the westward expansion of slavery into new states, was gaining prominence.
The election of a Republican, Abraham Lincoln, as President in 1860 sealed the deal. His victory, without a single Southern electoral vote, was a clear signal to the Southern states that they had lost all influence.
Feeling excluded from the political system, they turned to the only alternative they believed was left to them: secession, a political decision that led directly to war.
Video:
Causes of the Civil War
The causes of the Civil War and its cost to a young nation.
A female North Pacific Giant Octopus (Enteroctopus dofleini) lives three to four years; it lays thousands of eggs in a single bout and then dies. By contrast, a mature Coast Redwood Tree (Sequoia sempervirens) lives for many hundreds of years and produces millions of seeds each year (Figure 1). As these two examples illustrate, organisms differ dramatically in how they develop, the time they take to grow, when they become mature, how many offspring of a particular size they produce, and how long they live. Together, the age-, size-, or stage-specific patterns of development, growth, maturation, reproduction, survival, and lifespan define an organism's life cycle, its life history.
Figure 1:Â Diversity of life histories.
Top: A female North Pacific Giant Octopus (Enteroctopus dofleini). Bottom: A Coast Redwood Tree (Sequoia sempervirens).
Photos courtesy of (top) Bachrach44 via Wikimedia Commons, (bottom) Bernt Rostad via Flickr.
The principal aim of life history theory, a branch of evolutionary ecology, is to explain the remarkable diversity in life histories among species. But there is another, more compelling reason for why life history evolution is important: adaptation by natural selection is based on variation in Darwinian fitness among individuals, and since life history traits determine survival and reproduction they are the major components of fitness. The study of life history evolution is thus about understanding adaptation, the most fundamental issue in evolutionary biology.
Here we introduce the basics of life history theory and review what biologists have learned about life history evolution. For more in-depth coverage we refer to Stearns (1992), Roff (1992, 2002), Charlesworth (1994), and Flatt and Heyland (2011). Also see the Nature Education Knowledge articles by Shefferson (2010), Young (2010), and Fabian and Flatt (2011).
Life history theory seeks to explain how natural selection and other evolutionary forces shape organisms to optimize their survival and reproduction in the face of ecological challenges posed by the environment (Stearns 1992, Roff 1992, Stearns 2000), or as David Reznick has recently put it: "Life history theory predicts how natural selection should shape the way organisms parcel their resources into making babies" (Reznick 2010, p. 124). The theory does so by analyzing the evolution of fitness components, so-called life history traits, and how they interact: size at birth; growth pattern; age and size at maturity; number, size, and sex of offspring; age-, stage- or size-specific reproductive effort; age-, stage- or size-specific rates of survival; and lifespan.
The classical theory treats life history evolution as an optimization problem: given particular ecological factors (e.g., predators, nutrition) that affect an organism's probability of survival and reproduction, and given limiting constraints and trade-offs intrinsic to the organism, what are the optimal values and combinations of life history traits that maximize reproductive success? To find the solution to this problem we need to understand its "boundary conditions" (Stearns 2000): (1) how extrinsic, environmental factors affect survival and reproduction; and (2) how intrinsic connections among life history traits (trade-offs) and other constraints limit whether and how life history traits can evolve. Once these conditions have been understood and defined, life history models can be used to answer questions such as: How small or large should an organism grow? At what age and size should it mature? How many times should it reproduce? How many offspring should it produce and what size should they be? For how long should it reproduce and how long should it live?
Life history optimization problems are typically modeled by using the Euler-Lotka equation, which describes population growth rate (i.e., fitness) of a clonal genotype (or allele substitution) in continuous generation time as a function of its age at maturity, age at last reproduction, age-specific survival probability, and the expected age-specific number of offspring (Stearns 1992, Roff, 1992, Brommer 2000):
where α is the age at first reproduction, ω the age at last reproduction, lx the probability of surviving from birth to age class x, mx the expected number of offspring in age class x, and r the population growth rate or Malthusian parameter. The equation sums the probabilities of survival and reproduction over the entire lifetime of the individuals in the population and can then be solved for r. Note that in the context of life history theory r measures the growth rate or fitness of a clone or, in sexually reproducing organisms, the rate of spread of an allele that affects life history. Thus, the implicit assumption is that the modeled population consists of phenotypically and genetically identical individuals. If the population described by the Euler-Lotka equation is stationary (non-growing), r is zero and the equation becomes
or, if generation time is discrete,
where R0 is the expected number of daughters per female per lifetime (net reproductive rate). This equation is simpler than the continuous-time version and can be used whenever r is zero or close to zero; for stable populations that do not change in size, R0 is the appropriate fitness measure (Stearns 1992, Roff 1992, Brommer 2000). Using this framework, one can ask what particular combination of life history traits maximizes fitness, or how much fitness is affected when one of the traits is changed. This approach has been used with great success to predict the evolution of life history traits.
The evolution of life history traits by natural selection depends upon genetic variation on which selection can act to produce adaptations in response to the environment. The models mentioned above implicitly assume that life history evolution is not limited by a lack of genetic variation. Interestingly, however, the heritability (h2 = VA/VP = additive genetic variance divided by phenotypic variance), i.e. the proportion of phenotypic differences among individuals in a population that is explained by additive genetic differences among them, is usually small for life history traits. This low heritability could be caused by low amounts of additive genetic variance; yet, there exists ample genetic variation for life history traits in natural and laboratory populations. Consistent with the notion that fitness components harbor lots of genetic variation, many artificial selection experiments in the laboratory have successfully managed to cause evolutionary changes in life history traits in the predicted direction (Stearns 1992, Roff 1992, Houle 2001). One reason for the large VA of life history traits may be that they are highly complex, quantitative, polygenic traits influenced by many loci (Houle 1992).
But how can we reconcile the fact that VA is large while at the same time h2 is small? A likely reason for the low heritability of life history traits is that, although VA (the numerator) is large, VP (the denominator) is much larger than VA. Note that the phenotypic variance VP consists of VA, the additive genetic variance, plus a remainder, VR, that itself consists of all non-additive genetic sources of variation (i.e., due to dominance, epistasis, etc.) and phenotypic variation engendered by the environment (i.e., phenotypic plasticity, genotype by environment interactions; see below). Thus, life history traits probably have low heritability because they are influenced by many loci (which inflates both VA and VP) while at the same time harboring substantial amounts of residual variation VR, for example variation due to changes in the environment (which inflates VP but not VA) (Houle 1992, Houle 2001).
Moreover, although life history traits are under strong selection, which should exhaust genetic variance, several factors can maintain genetic variation for these traits, including mutation-selection balance, environmental heterogeneity and genotype by environment interactions, and negative genetic correlations (Stearns 1992, Roff 1992, Houle 2001). However, despite typically large amounts of life history variation, life history evolution is also subject to constraints.
Fitness would obviously be maximal if survival and reproduction would be maximal at all ages, stages, or sizes of an organism. In principle then, the basic problem of life history evolution is trivial: all life history traits should always evolve so as to maximize survival and reproduction and thus fitness (Houle 2001). This would very rapidly lead to the evolution of "Darwinian demons" (Law 1979) that would take over the world, i.e. organisms that start to reproduce as soon as they are born, produce an infinite number of offspring, and live forever. Such organisms, however, do not exist in the real world: Resources are finite, and life history traits are subject to intrinsic trade-offs and other types of constraints, so natural selection cannot maximize life history traits — and thus fitness — beyond certain limits. We call such limits evolutionary constraints (Stearns 1992, Houle 2001); as mentioned above, they represent the intrinsic "boundary condition" we must understand to predict life history evolution.
One of the most important types of constraint are life history trade-offs (Stearns 1992, Roff 1992, Flatt and Heyland 2011). A trade-off exists when an increase in one life history trait (improving fitness) is coupled to a decrease in another life history trait (reducing fitness), so that the fitness benefit through increasing trait 1 is balanced against a fitness cost through decreasing trait 2 (Figure 2A). (Note that trade-offs can also involve more than two traits.) At the genetic level, such trade-offs are thought to be caused by alleles with antagonistic pleiotropic effects or by linkage disequilibrium between loci.
Trade-offs are typically described by negative phenotypic or genetic correlations between fitness components among individuals in a population (Figure 2A). If the relationship is genetic, a negative genetic correlation is predicted to limit (i.e. to slow down or prevent) the evolution of the traits involved. Thus, a genetic trade-off exists in a population when an evolutionary change in a trait that increases fitness is linked to an evolutionary change in another trait that decreases fitness. The existence of genetic correlations can be established through quantitative genetic breeding designs or through correlated phenotypic responses to selection. For example, direct artificial selection for extended lifespan in genetically variable laboratory populations of fruit flies (Drosophila melanogaster) causes the evolution of increased adult lifespan (sometimes in 10 or fewer generations), but this evolutionary increase in longevity is coupled to decreased early reproduction (e.g., Zwaan et al. 1995). This suggests that lifespan and early reproduction are genetically negatively coupled, e.g. through antagonistic pleiotropic alleles (e.g., Flatt 2011, Fabian and Flatt 2011).
At the physiological level, trade-offs are caused by competitive allocation of limited resources to one life history trait versus the other within a single individual, for example when individuals with higher reproductive effort have a shorter lifespan or vice versa (Figure 2B). A helpful way to think resource allocation trade-offs is to imagine a life history as being a finite pie, with the different slices representing how an organism divides its resources among growth, storage, maintenance, survival, and reproduction (Reznick 2010; Figure 2C). The essential problem is this: given the ecological circumstances, and the fact that making one slice larger means making another one smaller, what is the best way to split the pie? Note that since resource allocation trade-offs might have a genetic basis, and since different genotypes may differ in aspects of resource allocation, the genetic and physiological views of trade-offs are not necessarily incompatible. However, physiological trade-offs at the individual level do not always translate into genetic (evolutionary) trade-offs at the population level. For instance, when the physiological (within-individual) trade-off is genetically fixed ("hard-wired") among all individuals within the population, all individuals will exhibit the same negative physiological relationship between two life history traits but the genetic correlation among individuals would be zero (Stearns 1989, Stearns 1992).
Figure 2:Â Life history trade-offs.
Top (A): A negative genetic (or phenotypic) correlation, i.e. a trade-off, between reproduction (e.g., number of eggs produced) and adult survival, one of the most commonly found negative relationships between life history traits. Middle (B): The so-called Y-model of resource allocation trade-offs. In this example, a limited resource (e.g., a nutrient) is acquired and differentially (competitively) allocated (invested) into physiological processes that affect survival at the expense of investment into reproductive functions (e.g., egg production, fecundity). Bottom (C): A useful way of thinking about resource allocation trade-offs is to imagine the life history as being a finite pie. See text for further details.
The book by Stearns (1992) lists 45 possible trade-offs among 10 major life history traits, and many more can be envisaged to exist. Those trade-offs that have received most attention include (1) current reproduction versus survival; (2) current versus future reproduction; (3) current reproduction versus parental growth; (4) current reproduction versus parental condition; and (5) number versus size of offspring.
Some of the best evidence for genetically based life history trade-offs comes from artificial selection and experimental evolution experiments carried out in Drosophila (see reviews in Stearns and Partridge 2001, Flatt and Schmidt 2009, Flatt 2011). In summary, many experiments have found: a negative correlation between early fecundity and adult lifespan; a positive correlation between developmental time and body size; a positive correlation between either developmental time or body size with early fecundity; and a negative correlation between early and late fecundity.
Other constraints on life histories that prevent natural selection from attaining a particular fitness optimum can involve biophysical, biochemical and structural factors, developmental properties of the organism, phylogenetic and historical contingencies, or simply a lack of genetic variation (Stearns 1992, Houle 2001).
Genetic variation and constraints are not the only factors affecting the expression and evolution of life history traits. Another important issue is that life history variation is often strongly influenced by the environment (e.g., temperature, nutrition, predators,), a phenomenon called phenotypic plasticity, i.e. the ability of a single genotype (or clone) to produce different phenotypes across different environments (Stearns 1992, Roff 1997, Pigliucci 2001, DeWitt and Scheiner 2004). The plasticity of a specific genotype can be conceptually described by a mathematical function called a reaction norm, i.e. a line or curve that relates the phenotypes produced by this genotype to changes in the environment it experiences (Figure 3A).
Figure 3:Â Life history plasticity.
Top (A). Phenotypic plasticity is often visualized using so-called reaction norms, curves that relate phenotypes and environments for a specific genotype. An example of a single reaction norm for body size in fruit flies (Drosophila), relating changes in ambient temperature during development to the adult body size phenotypes produced by a single fly genotype. Bottom (B): Genetic variation among genotypes in phenotypic plasticity manifests itself as a bundle of reaction norms with different slopes, i.e. the reaction norms are on average non-parallel. Such a pattern is also called genotype by environment interaction (GxE). Shown here is a case of particularly strong GxE, with the reaction norms of three genotypes crossing each other, a pattern that changes the relative ranking of the phenotypes across environments.
The importance of such plasticity in life history evolution is at least three-fold (Stearns and Koella 1986, Stearns et al. 1991, Stearns 1992, Nylin and Gotthard 1998, DeWitt and Scheiner 2004, Flatt 2005): (1) since plasticity modulates the phenotypic expression of genetic variation for single life history traits and of genetic correlations for pairs of traits, it affects the genetic response to selection across environments; (2) if there exists adaptive variation among genotypes for the plastic response, selection can produce an optimal reaction norm that maximizes fitness across environments; and (3) plasticity of a specific trait may homeostatically buffer the organism against environmentally-induced changes in other traits so that organismal performance and thus fitness is optimized.
Many life history traits (e.g., age at maturity, fecundity) exhibit a high degree of plasticity, and there is often significant genetic variation for plasticity in natural populations, i.e. genotypes have different reaction norms, a phenomenon called genotype by environment interaction (GxE) (Figure 3B). Moreover, not only single traits but also correlations between traits can be plastic, and different environments can change the slope and/or sign of the trait correlation (Stearns et al. 1991, Stearns 1992). In spadefoot toads (Scaphiophus couchii), for example, individuals that develop in ponds of short duration have a shorter larval period and a smaller body size at metamorphosis (with the traits being negatively correlated) than individuals that develop in ponds of long duration (with the traits being positively correlated) (Newman 1988, Stearns et al. 1991).
Having discussed the optimality modeling approach and the factors that influence the expression of life history traits, we turn now to discussing some major predictions for the evolution of life histories (for details see Stearns 1992, Roff 1992, Charlesworth 1994, Stearns 2000, Roff 2002).
At what age and size should an organism mature? A genotype's reproductive success depends strongly on its growth rate and — as a consequence of growth — on its age and size at maturity. To predict the optimal age and size at maturity we must understand the relative costs and benefits (in terms of mortality and reproduction) of either maturing early or late and of either growing large or staying small. The benefits of one "strategy" are the costs of the other, and vice versa. The benefits of maturing earlier and at a smaller size (i.e., the costs of maturing later and at larger size) include: (1) a higher probability of survival to maturity because of a shorter duration of the risky developmental and juvenile period, and (2) a shorter generation time which allows parents to produce offspring that are born earlier and that start to reproduce sooner. Thus, high juvenile mortality, for example, should favor the evolution of earlier maturity. Conversely, the benefits of maturing later and at a larger size (i.e., the costs of maturing earlier and at a smaller size) include: (1) longer growth which leads to larger size at maturity and thus increased fecundity (since fecundity often increases with size), (2) lower adult mortality (and thus potentially higher lifetime fecundity) due to a larger size (mortality due to predators is often lower for larger individuals), and (3) higher quality offspring (e.g., increased investment per offspring, better parental care) which improves survival of the offspring produced.
How many offspring should an organism produce? A good starting point to address this question is the "Lack clutch", a concept that goes back to the ornithologist David Lack (1947). Lack's basic insight was that birds should optimize their clutch size by maximizing the number of fledged (surviving) offspring. Deviations from this optimal clutch size would lower reproductive success: if parents produce too large a clutch, they may not be able to support and rear all their offspring, with some or all of them dying, whereas if they produce too small a clutch, the number of fledged offspring may be lower than what the parents could support (Figure 4). Although Lack was correct in his assertion that fitness is often maximized at intermediate investment, clutch sizes are typically smaller than what the Lack clutch predicts. This is because the concept ignores several factors that can reduce clutch size, including parental mortality, future reproduction, the rate of grandchildren production, and parent-offspring conflict. For example, the existence of trade-offs between current reproduction and parental survival, current and future reproduction, or the number and size of offspring can cause deviations from the Lack clutch, and models that take such factors into account usually yield a better fit with observed clutch size than the Lack clutch. For an excellent empirical study of optimal clutch size see the study by Daan et al. (1990) on European kestrels.
Figure 4:Â The Lack clutch.
The "Lack clutch" is defined as the clutch size that maximizes the number of fledged (surviving) offspring, assuming that offspring mortality is a function of clutch size. The trade-off between clutch size and offspring survival leads to an intermediate optimum in reproductive effort.
How often should an organism reproduce? Should it be semelparous (i.e., reproduce only once) or iteroparous (i.e., reproduce several times) (Figure 5; also see Young 2010)? Theory suggests that iteroparity and the evolution of increased reproductive lifespan are favored when adult survival is high and when adult fecundity or juvenile survival is low: high (or non-variable) adult survival increases the number of reproductive events per lifetime, and low (or variable) fecundity or juvenile survival cause fitness losses that select for increased compensatory reproductive effort. Conversely, semelparity and the evolution of decreased reproductive lifespan are favored when adult survival is low and juvenile survival is high. Thus, high (or non-variable) adult relative to juvenile survival favors iteroparity and lengthens reproductive lifespan while high (or variable) adult relative to juvenile mortality favors semelparity and shortens reproductive lifespan. Semelparous organisms typically have higher reproductive effort than iteroparous organisms.
Figure 5:Â Semelparity versus iteroparity.
Top: Organisms such as the octopus, the agave, or the marsupial mammal Antechinus reproduce only once per life and are therefore semelparous. From left to right: Octopus vulgaris, Agave tequilana, Antechinus agilis. Bottom: Organisms that reproduce more than once in their life are called iteroparous, a common life history strategy for example among birds, mammals including humans, insects, and many other species. From left to right: a small ground finch (Geospiza fuliginosa), a Madagascan family, and a yellow fever mosquito (Aedes aegypti).
The above considerations are aspects of a more general issue called the "general life history problem" or "reproductive effort model" (Schaffer 1983, Stearns 1992, Roff 1992, Charlesworth 1994): given that reproduction has both benefits (i.e., offspring production) and costs (e.g., decreased future reproduction, increased parental or offspring mortality), what is the optimal reproductive investment that maximizes fitness? Many theoretical and empirical studies have addressed this problem; some of the major conclusions from this work are (see Stearns 1992, Roff 1992, Charlesworth 1994): (1) reproductive effort often, but not always, increases with age because the cost of current reproduction in terms of future reproduction is expected to decrease with age (since the number of future reproductive events where costs may manifest themselves declines with age); (2) if reproductive effort yields decreasing returns or if mortality increases as the effort increases, intermediate reproductive investment and iteroparity are favored; otherwise, maximal reproductive effort and semelparity are favored; (3) if mortality increases in all age classes, reproductive effort increases early in life and age at maturity decreases; similarly, if adult mortality increases, age at maturity should decrease; and (4) if mortality increases after a particular age (or in one specific age class), reproductive effort increases before and decreases after that age. As particularly beautiful tests of such reproductive effort models we refer the reader to the field and laboratory experiments of David Reznick and colleagues on Trinidad guppies (e.g., Reznick et al. 1990).
How long should an organism live (also see Fabian and Flatt 2011)? The evolution of lifespan can be viewed as a balance between selection for increased reproductive lifespan (and thus potentially increased reproductive success) and aging (i.e., intrinsic age-dependent increase in mortality). The benefits of evolving a longer reproductive lifespan include (also see above): (1) a higher number of reproductive events (and thus offspring) per lifetime if extrinsic adult mortality is low, (2) sufficient time to reproductively compensate for offspring lost due to high juvenile mortality, and (3) decreased reproductive uncertainty due to high variation in juvenile mortality from one round of reproduction to the next, again by being able to compensate for lost offspring. These effects are counteracted by those that increase adult mortality (e.g., survival costs of reproduction; aging) relative to juvenile mortality. Thus, increases in the mean (and/or variance) of adult relative to juvenile mortality tend to favor a shorter reproductive lifespan and semelparity, whereas decreases in the mean (and/or variance) of adult relative to juvenile mortality tend to favor longer reproductive lifespan and iteroparity.
Today many of these predictions of life history theory are well supported by evidence; we shall end this article by giving an example of a particularly elegant experiment that has confirmed the major predictions of the "general life history problem".
To test the basic tenets of life history theory, Stearns et al. (2000) used an outbred population of fruit flies (D. melanogaster) to establish two sets of replicate "experimental evolution" lines: three lines were exposed to a high adult mortality treatment (HAM; by randomly killing 90% of the flies twice per week) and three lines to a low adult mortality treatment (LAM; by killing 10% of the flies twice per week). After four years of experimental evolution under these conditions in the lab, Stearns and collaborators measured the life history phenotypes of all lines in both treatments to examine the flies' evolutionary responses to high versus low extrinsic mortality. The results of this long-term experiment were both clear-cut and intriguing, confirming the theoretical predictions: fruit flies that had evolved under HAM conditions developed more rapidly as larvae, eclosed earlier and at a smaller size as adults, had higher early peak fecundity, and showed a shorter lifespan than the LAM flies which evolved the opposite suite of adaptations. In other words, flies evolving in a highly dangerous environment responded evolutionarily by speeding up their development, decreasing their age and size at maturity, laying more eggs earlier, and living shorter: they adapted to high levels of random mortality by shifting their reproductive effort to earlier ages and by compressing their entire life history into a shorter lifespan. Thus, similar to the findings by Reznick et al. (1990) in guppies, these results confirm the major predictions of life history theory, in particular the major role of extrinsic adult mortality in shaping the evolution of growth, maturation, reproduction, and aging.
Here we have introduced the basics of life history theory. Life history theory attempts to understand how natural selection designs organisms to achieve reproductive success, given knowledge of how selective factors in the environment (i.e., extrinsic mortality) and factors intrinsic to the organism (i.e., trade-offs, constraints) affect survival and reproduction. By using a variety of theoretical and empirical methods, and in particular by applying optimality thinking, life history theorists have derived major predictions about the evolution of the major life history traits, including age and size at maturity, the number and size of offspring, age- or size-specific reproductive effort, reproductive lifespan, and aging. Based on these predictions, and by testing them in field and laboratory experiments, for example in flies, fish, or birds, life history biologists have provided us with some compelling answers to fundamental questions such as: How fast should an organism develop? At what age and size should it mature? How many offspring should it have and how large should they be? Should it reproduce once or more than once? And how long should it live? Through addressing these problems life history theory has made a major impact on our understanding of adaptation by natural selection, the most fundamental issue in all of evolutionary biology.From disaster preparedness to nanoscience to food security, Drexel's Department of History is embroiled in some of the most critical issues of our day.
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